Why create diverse characters for learning scenarios? Our characters should reflect the diversity of our audience. When in doubt, I tend to err on the side of being more diverse in my representation rather than more homogeneous. I’d rather show an aspiration of diversity, even if organizations haven’t reached that goal of diverse representation in real life yet.
In response to my post on Name Generators for Learning Scenarios, someone asked, “Does it really matter if we choose John instead of Bob?”
Different names have different implications of age, race, background, etc. If you only ever call your characters Bob and John, you never represent women or anyone that isn’t a white, middle-aged, middle class man. If your audience is mostly 20-something and Latinx or Asian, they’re going to have a harder time identifying with your characters.
Plus, it’s not just names. The images we use to depict characters matter too. We can model diversity and inclusion in our work.
Women and men
For most learning scenarios, I aim for a roughly 50/50 split of women and men because that’s what the world population looks like. Your workplace might actually be closer to 60/40, but in general, an even split is a good goal.
In some industries, an even split isn’t realistic. Firefighters, for example, are overwhelmingly male. I wouldn’t try to create a 50/50 split if I was designing a course for firefighters. I would, however, try to have at least one or two female characters.
Women should also be represented as managers, mentors, and leaders. I create a fair number of courses with two narrators like my coaching and mentoring course. In those courses, one character is a mentor explaining content to someone less experienced. Usually, I use a woman as the mentor. However, if I create multiple courses for that client, then I try to alternate male/female for the role of the mentor.
Trans and nonbinary
One recent trend in elearning is a shift to include trans and nonbinary characters. In 2021, I had two different clients specifically request nonbinary characters for scenarios. For one of those projects, I used illustrated characters in the “Designer Realistic” style from the eLearning Art library. I started with two of their existing characters, and then combined features to create some character options for my client. I used the male face shape and eyebrows, but the female mouth and earrings. The hair options came from two different female characters. Because these are SVG images with separate layers for each feature, it’s easy to mix and match to customize your characters.
An informal poll in a LinkedIn group a while back showed that most IDs and eLearning developers are already trying to represent diversity in race in the images in their courses. However, this can be a challenge with stock photos. Trina Rimmer provides excellent suggestions for how to work around the lack of diversity in her recent article The Lack of Diversity in Stock Images Hurts Your eLearning—and What to Do About It. Her ideas include taking your own images, altering stock photos, and using illustrations that don’t obviously show race. I’ve also seen silhouettes used for that same purpose.
I adjust the racial diversity of my characters and examples depending on the audience. For example, I wrote a course on improving educational outcomes for Native Americans. Native Americans make up about 1% of the US population, but they make up less than 1% of the models on stock photo sites. Stock photos of Native Americans often show exactly the kinds of stereotypes we were trying to combat in that course. It took some creativity and diligent filtering to find the right images.
Similarly, I have worked with another client who has a heavily Latinx and Native American population. Therefore, the images and names for those projects include a much higher percentage of Latinx and Native Americans.
As I explained in my previous post, I use name generators to help me create more authentic names of Latinx or Asian characters. For the Native American course, the SME provided the name of one major character, and I researched common names for another character.
A few years ago, I created a course on accommodations for disabilities in child care settings. That course included numerous examples and short scenarios, most of which also included images. While I didn’t need multiple poses of the same person, I did need a wide range of images of children with different disabilities playing and interacting with others.
When I was searching for those images, one strategy that worked was to search for specific terms rather than generic ones like “disability” or “accessibility.” Searches for “Downs syndrome,” “leg brace,” “hearing aid,” or “cerebral palsy” provided better results.
Characters with disabilities shouldn’t only appear in scenarios focused on disabilities though. This is another aspect of diversity and inclusion, just like gender and race. I’m beginning to see this as something my clients request in scenarios, and I hope that trend continues.
Tricia Ransom and Judy Katz have collected a number of resources for their presentations on “Wonder Woman, Wakanda, and Work: Development Solutions for Representation.”
I often use stock images for mini-scenarios. If I need multiple photos of the same character, I often use cutout characters from the eLearning Art library. Especially for business people, their library has diversity of gender, race, age, ability, and body type. Not everyone in their library is a skinny model; it’s more realistic.
As I mentioned earlier, I also use illustrated characters. Customizable characters can make it easier to reflect diversity in characters.
Check out these resources for more diverse characters and images. These are generally more useful for scenarios where you only need one or two images, not a series of multiple poses with the same characters.
- 19 Great Resources for Diverse Stock Photos
- Black Illustrations: Buy packs of illustrations related to a theme
- Nappy: Beautiful photos of Black and Brown people
- Photo Ability: Inclusive imagery of people with disabilities
- Disability Images: Search by specific disabilities or topics
Are there exceptions to aiming for diversity in characters? Overall, it depends on your audience. The person who asked why it matters if we call characters Bob or John lives and works in an Eastern European country with a fairly homogeneous population. He says he doesn’t use diverse examples; he uses traditional names in his country. That may be the best choice for his audience (although I’d still argue for gender diversity in images and characters).
In the US, most organizations expect some diversity in the images for their courses. My experience with global companies has shown the same to be true in those settings, often even more so.
What do you do?
If you create characters for learning scenarios, are you conscious of the diversity of those characters? How do you reflect your audience in your examples? I’m especially interested in hearing experiences from people outside the US; I wonder if the cultural standards differ in other countries.
Originally published 9/23/2015. Revised 1/3/2022.